Cerebral organoids display dynamic clonal growth and tunable tissue replenishment.

During brain development, neural progenitors expand through symmetric divisions before giving rise to differentiating cell types via asymmetric divisions. Transition between those modes varies among individual neural stem cells, resulting in clones of different sizes. Imaging-based lineage tracing allows for lineage analysis at high cellular resolution but systematic approaches to analyse clonal behaviour of entire tissues are currently lacking.

Neutral competition explains the clonal composition of neural organoids.

Neural organoids model the development of the human brain and are an indispensable tool for studying neurodevelopment. Whole-organoid lineage tracing has revealed the number of progenies arising from each initial stem cell to be highly diverse, with lineage sizes ranging from one to more than 20,000 cells. This high variability exceeds what can be explained by existing stochastic models of corticogenesis and indicates the existence of an additional source of stochasticity.

Genome replication in asynchronously growing microbial populations.

Biological cells replicate their genomes in a well-planned manner. The DNA replication program of an organism determines the timing at which different genomic regions are replicated, with fundamental consequences for cell homeostasis and genome stability. In a growing cell culture, genomic regions that are replicated early should be more abundant than regions that are replicated late.

Critical Growth of Cerebral Tissue in Organoids: Theory and Experiments.

We develop a Fokker-Planck theory of tissue growth with three types of cells (symmetrically dividing, asymmetrically dividing, and nondividing) as main agents to study the growth dynamics of human cerebral organoids. Fitting the theory to lineage tracing data obtained in next generation sequencing experiments, we show that the growth of cerebral organoids is a critical process. We derive analytical expressions describing the time evolution of clonal lineage sizes and show how power-law distributions arise in the limit of long times due to the vanishing of a characteristic growth scale.

Genome-wide screening in pluripotent cells identifies Mtf1 as a suppressor of mutant huntingtin toxicity.

Huntington's disease (HD) is a neurodegenerative disorder caused by CAG-repeat expansions in the huntingtin (HTT) gene. The resulting mutant HTT (mHTT) protein induces toxicity and cell death via multiple mechanisms and no effective therapy is available. Here, we employ a genome-wide screening in pluripotent mouse embryonic stem cells (ESCs) to identify suppressors of mHTT toxicity.

A human tissue screen identifies a regulator of ER secretion as a brain-size determinant.

Loss-of-function (LOF) screens provide a powerful approach to identify regulators in biological processes. Pioneered in laboratory animals, LOF screens of human genes are currently restricted to two-dimensional cell cultures, which hinders the testing of gene functions requiring tissue context. Here, we present CRISPR-lineage tracing at cellular resolution in heterogeneous tissue (CRISPR-LICHT), which enables parallel LOF studies in human cerebral organoid tissue.

Insertion Pool Sequencing for Insertional Mutant Analysis in Complex Host-Microbe Interactions.

Insertional mutant libraries of microorganisms can be applied in negative depletion screens to decipher gene functions. Because of underrepresentation in colonized tissue, one major bottleneck is analysis of species that colonize hosts. To overcome this, we developed insertion pool sequencing (iPool-Seq).

In vivo insertion pool sequencing identifies virulence factors in a complex fungal-host interaction.

Large-scale insertional mutagenesis screens can be powerful genome-wide tools if they are streamlined with efficient downstream analysis, which is a serious bottleneck in complex biological systems. A major impediment to the success of next-generation sequencing (NGS)-based screens for virulence factors is that the genetic material of pathogens is often underrepresented within the eukaryotic host, making detection extremely challenging. We therefore established insertion Pool-Sequencing (iPool-Seq) on maize infected with the biotrophic fungus U.

TRUmiCount: correctly counting absolute numbers of molecules using unique molecular identifiers.

Motivation: Counting molecules using next-generation sequencing (NGS) suffers from PCR amplification bias, which reduces the accuracy of many quantitative NGS-based experimental methods such as RNA-Seq. This is true even if molecules are made distinguishable using unique molecular identifiers (UMIs) before PCR amplification, and distinct UMIs are counted instead of reads: Molecules that are lost entirely during the sequencing process will still cause underestimation of the molecule count, and amplification artifacts like PCR chimeras create phantom UMIs and thus cause over-estimation.

Results: We introduce the TRUmiCount algorithm to correct for both types of errors.